2008
DOI: 10.1117/1.3028347
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Three-dimensional projective invariants of points from multiple images

Abstract: Invariance is widely used in 3-D object recognition due to its good performance on change of viewpoint. A method of computing 3-D invariants of seven points from two images is presented, which can be used to achieve reliable recognition of a 3-D object and scene. Based on the matrix representation of the projective transformation between 3-D and 2-D points, geometric invariants are derived by the determinant ratios. First, the general ratiocination about invariants is represented. Second, the general method of… Show more

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Cited by 2 publications
(1 citation statement)
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“…The second method is phase error compensation by interpolation fitting and Look-Up Table (LUT). Chen, et al were proposed method adopts smoothing spline approximation to precisely extract the specific system phase error from the reference phase according to the system's phase distribution properties [10]. But the spline interpolation fitting is multiple iterations, and time-consuming is expensive.…”
Section: Introductionmentioning
confidence: 99%
“…The second method is phase error compensation by interpolation fitting and Look-Up Table (LUT). Chen, et al were proposed method adopts smoothing spline approximation to precisely extract the specific system phase error from the reference phase according to the system's phase distribution properties [10]. But the spline interpolation fitting is multiple iterations, and time-consuming is expensive.…”
Section: Introductionmentioning
confidence: 99%